scholarly journals JAMMIT Analysis Defines 2 Semi-Independent Immune Processes Common to 29 Solid Tumors

2021 ◽  
Author(s):  
Emory Zitello ◽  
Michael Vo ◽  
Shaoqiu Chen ◽  
Scott Bowler ◽  
Vedbar Khadka ◽  
...  
Keyword(s):  
Solid Tumors ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Published Data ◽  
Molecular Features ◽  
Solid Malignancies ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Bioinformatic Approaches ◽  
Tumor Types

AbstractImmunophenotype of solid tumors has relevance to cancer immunotherapy, as not all patients respond optimally to treatment utilizing monoclonal antibodies. Bioinformatic studies have failed to clearly identify tumor immunophenotype in a way that encompasses a wide variety of tumor types and highlights fundamental differences among them, complicating prediction of patient clinical response. The novel JAMMIT algorithm was used to analyze mRNA data for 33 cancer types in The Cancer Genome Atlas (TCGA). We found that B cells and T cells constitute the principal source of variation in most patient cohorts, and that virtually all solid malignancies formed three hierarchical clustering patterns with similar molecular features. The second main source of variability in transcriptomic studies we attribute to monocytes. We identified the three tumor types as TC1-mediated, TC17-mediated and non-immunogenic immunophenotypes and used a 3-gene signature to approximate infiltration by agranulocytes. Methods of in silico validation such as pathway analysis, Cibersort and published data from treated cohorts were used to substantiate these findings. Monocytic infiltrate is found to be related to patient survival according to immunophenotype, important differences in some solid tumors are identified and deficiencies of common bioinformatic approaches relevant to diagnosis are detailed by this work.

scholarly journals Epstein-Barr Virus-Positive Cancers Show Altered B-Cell Clonality

mSystems ◽  
2018 ◽  
Vol 3 (5) ◽  
Author(s):  
Sara R. Selitsky ◽  
David Marron ◽  
Lisle E. Mose ◽  
Joel S. Parker ◽  
Dirk P. Dittmer
Keyword(s):  
B Cells ◽  
B Cell ◽  
Epstein Barr Virus ◽  
The Cancer Genome Atlas ◽  
Barr Virus ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Epstein Barr ◽  
Tumor Types ◽  
Genome Atlas

ABSTRACTEpstein-Barr virus (EBV) is convincingly associated with gastric cancer, nasopharyngeal carcinoma, and certain lymphomas, but its role in other cancer types remains controversial. To test the hypothesis that there are additional cancer types with high prevalence of EBV, we determined EBV viral expression in all the Cancer Genome Atlas Project (TCGA) mRNA sequencing (mRNA-seq) samples (n= 10,396) from 32 different tumor types. We found that EBV was present in gastric adenocarcinoma and lymphoma, as expected, and was also present in >5% of samples in 10 additional tumor types. For most samples, EBV transcript levels were low, which suggests that EBV was likely present due to infected infiltrating B cells. In order to determine if there was a difference in the B-cell populations, we assembled B-cell receptors for each sample and found B-cell receptor abundance (P≤ 1.4 × 10−20) and diversity (P≤ 8.3 × 10−27) were significantly higher in EBV-positive samples. Moreover, diversity was independent of B-cell abundance, suggesting that the presence of EBV was associated with an increased and altered B-cell population.IMPORTANCEAround 20% of human cancers are associated with viruses. Epstein-Barr virus (EBV) contributes to gastric cancer, nasopharyngeal carcinoma, and certain lymphomas, but its role in other cancer types remains controversial. We assessed the prevalence of EBV in RNA-seq from 32 tumor types in the Cancer Genome Atlas Project (TCGA) and found EBV to be present in >5% of samples in 12 tumor types. EBV infects epithelial cells and B cells and in B cells causes proliferation. We hypothesized that the low expression of EBV in most of the tumor types was due to infiltration of B cells into the tumor. The increase in B-cell abundance and diversity in subjects where EBV was detected in the tumors strengthens this hypothesis. Overall, we found that EBV was associated with an increased and altered immune response. This result is not evidence of causality, but a potential novel biomarker for tumor immune status.

scholarly journals Novel Insights into Epigenetic Regulation of IL6 Pathway: In Silico Perspective on Inflammation and Cancer Relationship

2021 ◽  
Vol 22 (18) ◽  
pp. 10172
Author(s):  
Saverio Candido ◽  
Barbara Maria Rita Tomasello ◽  
Alessandro Lavoro ◽  
Luca Falzone ◽  
Giuseppe Gattuso ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Epigenetic Regulation ◽  
Computational Analysis ◽  
The Cancer Genome Atlas ◽  
Post Translational Modifications ◽  
Pathway Gene ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Tumor Types

IL-6 pathway is abnormally hyperactivated in several cancers triggering tumor cell growth and immune system inhibition. Along with genomic mutation, the IL6 pathway gene expression can be affected by DNA methylation, microRNAs, and post-translational modifications. Computational analysis was performed on the Cancer Genome Atlas (TCGA) datasets to explore the role of IL6, IL6R, IL6ST, and IL6R transmembrane isoform expression and their epigenetic regulation in different cancer types. IL6 was significantly modulated in 70% of tumor types, revealing either up- or down-regulation in an approximately equal number of tumors. Furthermore, IL6R and IL6ST were downregulated in more than 10 tumors. Interestingly, the correlation analysis demonstrated that only the IL6R expression was negatively affected by the DNA methylation within the promoter region in most tumors. Meanwhile, only the IL6ST expression was extensively modulated by miRNAs including miR-182-5p, which also directly targeted all three genes. In addition, IL6 upregulated miR-181a-3p, mirR-214-3p, miR-18a-5p, and miR-938, which in turn inhibited the expression of IL6 receptors. Finally, the patients’ survival rate was significantly affected by analyzed targets in some tumors. Our results suggest the relevance of epigenetic regulation of IL6 signaling and pave the way for further studies to validate these findings and to assess the prognostic and therapeutic predictive value of these epigenetic markers on the clinical outcome and survival of cancer patients.

scholarly journals Identifying Interaction Clusters for MiRNA and MRNA Pairs in TCGA Network

Genes ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 702 ◽  
Author(s):  
Dai ◽  
Ding ◽  
Liu ◽  
Xu ◽  
Jiang ◽  
...  
Keyword(s):  
Messenger Rna ◽  
The Cancer Genome Atlas ◽  
Biological Functions ◽  
Significant Cluster ◽  
Scoring Method ◽  
Nonalcoholic Fatty Liver ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Liver Hepatocellular Carcinoma ◽  
Tumor Types

Existing methods often fail to recognize the conversions for the biological roles of the pairs of genes and microRNAs (miRNAs) between the tumor and normal samples. We have developed a novel cluster scoring method to identify messenger RNA (mRNA) and miRNA interaction pairs and clusters while considering tumor and normal samples jointly. Our method has identified 54 significant clusters for 15 cancer types selected from The Cancer Genome Atlas project. We also determined the shared clusters across tumor types and/or subtypes. In addition, we compared gene and miRNA overlap between lists identified in our liver hepatocellular carcinoma (LIHC) study and regulatory relationships reported from human and rat nonalcoholic fatty liver disease studies (NAFLD). Finally, we analyzed biological functions for the single significant cluster in LIHC and uncovered a significantly enriched pathway (phospholipase D signaling pathway) with six genes represented in the cluster, symbols: DGKQ, LPAR2, PDGFRB, PIK3R3, PTGFR and RAPGEF3.

scholarly journals Association of PD-1/PD-L axis expression with cytolytic activity, mutational load, and prognosis in melanoma and other solid tumors

2016 ◽  
Vol 113 (48) ◽  
pp. E7769-E7777 ◽  
Author(s):  
Ludmila Danilova ◽  
Hao Wang ◽  
Joel Sunshine ◽  
Genevieve J. Kaunitz ◽  
Tricia R. Cottrell ◽  
...  
Keyword(s):  
Predictive Biomarkers ◽  
Gene Signature ◽  
Cytolytic Activity ◽  
The Cancer Genome Atlas ◽  
Conditional Inference ◽  
Tumor Type ◽  
Mutational Load ◽  
Prognostic Features ◽  
Cancer Genome Atlas ◽  
Tumor Types

Programmed cell death protein-1 (PD-1)/programmed death ligand-1 (PD-L1) checkpoint blockade has led to remarkable and durable objective responses in a number of different tumor types. A better understanding of factors associated with the PD-1/PD-L axis expression is desirable, as it informs their potential role as prognostic and predictive biomarkers and may suggest rational treatment combinations. In the current study, we analyzedPD-L1,PD-L2,PD-1, and cytolytic activity (CYT) expression, as well as mutational density from melanoma and eight other solid tumor types using The Cancer Genome Atlas database. We found that in some tumor types,PD-L2expression is more closely linked toTh1/IFNGexpression and PD-1 and CD8 signaling thanPD-L1. In contrast, mutational load was not correlated with aTh1/IFNGgene signature in any tumor type.PD-L1,PD-L2,PD-1,CYTexpression, and mutational density are all positive prognostic features in melanoma, and conditional inference modeling revealedPD-1/CYTexpression (i.e., an inflamed tumor microenvironment) as the most impactful feature, followed by mutational density. This study elucidates the highly interdependent nature of these parameters, and also indicates that future biomarkers for anti–PD-1/PD-L1 will benefit from tumor-type–specific, integrated, mRNA, protein, and genomic approaches.

scholarly journals Pan-cancer characterization of metabolism-related biomarkers identifies potential therapeutic targets

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Guoshu Bi ◽  
Yunyi Bian ◽  
Jiaqi Liang ◽  
Jiacheng Yin ◽  
Runmei Li ◽  
...  
Keyword(s):  
Metabolic Reprogramming ◽  
The Cancer Genome Atlas ◽  
Score System ◽  
Molecular Features ◽  
Cancer Genome Atlas ◽  
Metabolic Heterogeneity ◽  
Tumor Types ◽  
Pan Cancer ◽  
Worse Prognosis

Abstract Background Generally, cancer cells undergo metabolic reprogramming to adapt to energetic and biosynthetic requirements that support their uncontrolled proliferation. However, the mutual relationship between two critical metabolic pathways, glycolysis and oxidative phosphorylation (OXPHOS), remains poorly defined. Methods We developed a “double-score” system to quantify glycolysis and OXPHOS in 9668 patients across 33 tumor types from The Cancer Genome Atlas and classified them into four metabolic subtypes. Multi-omics bioinformatical analyses was conducted to detect metabolism-related molecular features. Results Compared with patients with low glycolysis and high OXPHOS (LGHO), those with high glycolysis and low OXPHOS (HGLO) were consistently associated with worse prognosis. We identified common dysregulated molecular features between different metabolic subgroups across multiple cancers, including gene, miRNA, transcription factor, methylation, and somatic alteration, as well as investigated their mutual interfering relationships. Conclusion Overall, this work provides a comprehensive atlas of metabolic heterogeneity on a pan-cancer scale and identified several potential drivers of metabolic rewiring, suggesting corresponding prognostic and therapeutic utility.

scholarly journals TumorFusions: an integrative resource for reporting cancer-associated transcript fusions in 33 tumor types

2017 ◽  
Author(s):  
Xin Hu ◽  
Qianghu Wang ◽  
Floris Barthel ◽  
Ming Tang ◽  
Samirkumar Amin ◽  
...  
Keyword(s):  
The Cancer Genome Atlas ◽  
Whole Genome Sequencing Data ◽  
Fusion Genes ◽  
Sequencing Data ◽  
Structural Variations ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Tumor Types ◽  
Fusion Detection ◽  
Genome Atlas

Fusion genes, particularly those involving kinases, have been demonstrated as drivers and are frequent therapeutic targets in cancer1. Here, we describe our results on detecting transcript fusions across 33 cancer types from The Cancer Genome Atlas (TCGA), totaling 9,966 cancer samples and 648 normal samples2. Preprocessing, including read alignment to both genome and transcriptome, and fusion detection were carried out using a uniform pipeline3. To validate the resultant fusions, we also called somatic structural variations for 561 cancers from whole genome sequencing data. A summary of the data used in this study is provided in Table S1. Our results can be accessed per our portal at http://www.tumorfusions.org.

scholarly journals Deep Learning for Automatic Subclassification of Gastric Carcinoma Using Whole-Slide Histopathology Images

Cancers ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 3811
Author(s):  
Hyun-Jong Jang ◽  
In-Hye Song ◽  
Sung-Hak Lee
Keyword(s):  
Deep Learning ◽  
Relative Proportion ◽  
The Cancer Genome Atlas ◽  
Cancer Tissue ◽  
Mucinous Tumor ◽  
Receiver Operating Characteristic Curves ◽  
Tumor Tissues ◽  
Cancer Genome Atlas ◽  
Stomach Adenocarcinoma ◽  
Tumor Types

Histomorphologic types of gastric cancer (GC) have significant prognostic values that should be considered during treatment planning. Because the thorough quantitative review of a tissue slide is a laborious task for pathologists, deep learning (DL) can be a useful tool to support pathologic workflow. In the present study, a fully automated approach was applied to distinguish differentiated/undifferentiated and non-mucinous/mucinous tumor types in GC tissue whole-slide images from The Cancer Genome Atlas (TCGA) stomach adenocarcinoma dataset (TCGA-STAD). By classifying small patches of tissue images into differentiated/undifferentiated and non-mucinous/mucinous tumor tissues, the relative proportion of GC tissue subtypes can be easily quantified. Furthermore, the distribution of different tissue subtypes can be clearly visualized. The patch-level areas under the curves for the receiver operating characteristic curves for the differentiated/undifferentiated and non-mucinous/mucinous classifiers were 0.932 and 0.979, respectively. We also validated the classifiers on our own GC datasets and confirmed that the generalizability of the classifiers is excellent. The results indicate that the DL-based tissue classifier could be a useful tool for the quantitative analysis of cancer tissue slides. By combining DL-based classifiers for various molecular and morphologic variations in tissue slides, the heterogeneity of tumor tissues can be unveiled more efficiently.

scholarly journals Radiosensitivity index emerges as a potential biomarker for combined radiotherapy and immunotherapy

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Yang-Hong Dai ◽  
Ying-Fu Wang ◽  
Po-Chien Shen ◽  
Cheng-Hsiang Lo ◽  
Jen-Fu Yang ◽  
...  
Keyword(s):  
Dna Repair ◽  
Interferon Γ ◽  
The Cancer Genome Atlas ◽  
Differential Analysis ◽  
Macrophage Polarisation ◽  
Molecular Features ◽  
Kaplan Meier ◽  
M1 Macrophage ◽  
Potential Biomarker ◽  
Cancer Genome Atlas

AbstractIn the era of immunotherapy, there lacks of a reliable genomic predictor to identify optimal patient populations in combined radiotherapy and immunotherapy (CRI). The purpose of this study is to investigate whether genomic scores defining radiosensitivity are associated with immune response. Genomic data from Merged Microarray-Acquired dataset (MMD) were established and the Cancer Genome Atlas (TCGA) were obtained. Based on rank-based regression model including 10 genes, radiosensitivity index (RSI) was calculated. A total of 12832 primary tumours across 11 major cancer types were analysed for the association with DNA repair, cellular stemness, macrophage polarisation, and immune subtypes. Additional 585 metastatic tissues were extracted from MET500. RSI was stratified into RSI-Low and RSI-High by a cutpoint of 0.46. Proteomic differential analysis was used to identify significant proteins according to RSI categories. Gene Set Variance Analysis (GSVA) was applied to measure the genomic pathway activity (18 genes for T-cell inflamed activity). Kaplan-Meier analysis was performed for survival analysis. RSI was significantly associated with homologous DNA repair, cancer stemness and immune-related molecular features. Lower RSI was associated with higher fraction of M1 macrophage. Differential proteomic analysis identified significantly higher TAP2 expression in RSI-Low colorectal tumours. In the TCGA cohort, dominant interferon-γ (IFN-γ) response was characterised by low RSI and predicted better response to programmed cell death 1 (PD-1) blockade. In conclusion, in addition to radiation response, our study identified RSI to be associated with various immune-related features and predicted response to PD-1 blockade, thus, highlighting its potential as a candidate biomarker for CRI.

Identification of a lncRNA prognostic signature-related to stem cell index and its significance in colorectal cancer

2021 ◽  
Author(s):  
Xiao-Cheng Wang ◽  
Ya Liu ◽  
Fei-Wu Long ◽  
Liang-Ren Liu ◽  
Chuan-Wen Fan
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Prognostic Markers ◽  
The Cancer Genome Atlas ◽  
Prognostic Signature ◽  
Free Survival ◽  
Cancer Genome Atlas ◽  
Bioinformatic Approaches ◽  
Cell Phenotypes ◽  
The Relationship

Background: The relationship between long noncoding RNAs (lncRNAs) and the mRNA stemness index (mRNAsi) in colorectal cancer (CRC) is still unclear. Materials & methods: The mRNAsi, mRNAsi-related lncRNAs and their clinical significance were analyzed by bioinformatic approaches in The Cancer Genome Atlas (TCGA)-COREAD dataset. Results: mRNAsi was negatively related to pathological features but positively related to overall survival and recurrence-free survival in CRC. A five mRNAsi-related lncRNAs prognostic signature was further developed and showed independent prognostic factors related to overall survival in CRC patients, due to the five mRNAsi-related lncRNAs involved in several pathways of the cancer stem cells and malignant cancer cell phenotypes. Conclusion: The present study highlights the potential roles of mRNAsi-related lncRNAs as alternative prognostic markers.

scholarly journals RNA Exosome Component EXOSC4 Amplified in Multiple Cancer Types Is Required for the Cancer Cell Survival

2022 ◽  
Vol 23 (1) ◽  
pp. 496
Author(s):  
Kenzui Taniue ◽  
Tanzina Tanu ◽  
Yuki Shimoura ◽  
Shuhei Mitsutomi ◽  
Han Han ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Cell Viability ◽  
The Cancer Genome Atlas ◽  
Multiple Cancer ◽  
Pancreatic Cancer Cells ◽  
Cancer Cell Survival ◽  
Cellular Machinery ◽  
Cancer Types ◽  
Rna Exosome ◽  
Tumor Types

The RNA exosome is a multi-subunit ribonuclease complex that is evolutionally conserved and the major cellular machinery for the surveillance, processing, degradation, and turnover of diverse RNAs essential for cell viability. Here we performed integrated genomic and clinicopathological analyses of 27 RNA exosome components across 32 tumor types using The Cancer Genome Atlas PanCancer Atlas Studies’ datasets. We discovered that the EXOSC4 gene, which encodes a barrel component of the RNA exosome, was amplified across multiple cancer types. We further found that EXOSC4 alteration is associated with a poor prognosis of pancreatic cancer patients. Moreover, we demonstrated that EXOSC4 is required for the survival of pancreatic cancer cells. EXOSC4 also repressed BIK expression and destabilized SESN2 mRNA by promoting its degradation. Furthermore, knockdown of BIK and SESN2 could partially rescue pancreatic cells from the reduction in cell viability caused by EXOSC4 knockdown. Our study provides evidence for EXOSC4-mediated regulation of BIK and SESN2 mRNA in the survival of pancreatic tumor cells.

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